Most proteins are evolved to interact with a multitude of cellular molecules and thus contain a number of distinct domains, binding sites, and activities. Often, it is useful to the biochemist to reduce a specific aspect of a protein's function to just a peptide fragment. This can help to determine the minimal features of a protein required for a specific function such as binding, recognition by an enzyme, translocation, or folding.1-4 It may also be desirable to create a consensus peptide substrate for assay purposes,5, 6 or to use a peptide in place of a protein to facilitate crystallography of multiprotein complexes.7,8 For therapeutic applications, replacement of protein drugs with peptides having similar activity can improve tissue penetration and reduce immunogenicity.9,10 
One application of protein minimization to peptides is for the purpose of developing new protein labeling technologies. Size minimization of protein tags that direct the targeting of fluorescent probes11 can greatly reduce problems of tag interference with protein trafficking, folding, and interactions. Conversion of proteins to peptides without loss of the function of interest, however, is challenging for a number of reasons. First, the function may require secondary structure that is difficult to recapitulate in a peptide. Second, the function may require contributions from multiple, noncontiguous regions of a protein. Third, structural information is not available for many proteins, and in some cases, even the regions that contribute to a protein's relevant activity are not known. Fourth, due to their more flexible structure, peptide binding is often associated with a greater entropic penalty than is protein binding,12 making it more difficult to engineer high-affinity interactions. Numerous methods have been used to reduce proteins to peptides. Simple truncation and/or rational design can be successful,13-15 but is usually associated with at least a partial loss of activity and/or specificity. Peptide scanning16 or high-throughput screening17-19 approaches are more exhaustive, but library sizes are limited (typically 102-105), so it is difficult to identify optimal sequences.